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--- |
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license: apache-2.0 |
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tags: |
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- image-classification |
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- generated_from_trainer |
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datasets: |
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- cifar100 |
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metrics: |
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- accuracy |
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model-index: |
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- name: vit-base-beans-demo-v5 |
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results: |
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- task: |
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name: Image Classification |
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type: image-classification |
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dataset: |
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name: Cifar100 |
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type: cifar100 |
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args: cifar100 |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.8985 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# vit-base-beans-demo-v5 |
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This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the Cifar100 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4420 |
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- Accuracy: 0.8985 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 0.0002 |
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- train_batch_size: 16 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 4 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:| |
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| 1.08 | 1.0 | 3125 | 0.6196 | 0.8262 | |
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| 0.3816 | 2.0 | 6250 | 0.5322 | 0.8555 | |
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| 0.1619 | 3.0 | 9375 | 0.4817 | 0.8765 | |
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| 0.0443 | 4.0 | 12500 | 0.4420 | 0.8985 | |
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### Framework versions |
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- Transformers 4.19.2 |
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- Pytorch 1.11.0+cu113 |
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- Datasets 2.2.1 |
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- Tokenizers 0.12.1 |
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